1. Field of the Invention
The claimed invention relates generally to systems and methods for computerized medical imaging and analysis; and more particularly, to systems and methods for cell-based pattern recognition and machine learning as applied to microscopy images from tissue sections.
2. Description of the Related Art
Many computerized tissue analysis applications require that the analysis is performed only for cells of certain types, e.g. invasive tumor cells.
A pathologist can outline the regions-of-analysis that only include cells of interest, but this can be very time consuming and impractical when analyzing entire tissue sections.
An automated pattern recognition tool is needed that identifies cells in tissue that are of the type of interest.
The performance of a pattern recognition tool depends on its feature set. Pattern recognition tools that use general-purpose pixel-based feature sets can be used in a wide variety of applications. However these provide in many cases, only a sub-optimal performance for any particular application.
Different types of tissue have different looking cells and each cell compartment can be stained with different colors depending on the application. Any tissue analysis is therefore highly specific to its particular application.
The best feature set to identify cells of a certain type should be based on a characterization of the cells, which needs to be optimized for any particular application. However, conventional systems and methods have yet to apply such a feature set to yield a functional automated pattern recognition tool.